Level
Lead
Ort
Berlin
Arbeitsmodell
Hybrid, Onsite
Job Feld
Data, Back End
Anstellung
Vollzeit
Vertragsart
Unbefristetes Dienstverhältnis

Job Zusammenfassung

In dieser Rolle entwickelst du skalierbare Datenpipelines und Integrationen, um sicherzustellen, dass KI-Lösungen auf hochwertigen, vertrauenswürdigen Daten basieren und über robuste Zugriffs- und Verwaltungsstrukturen verfügen.

Job Technologien

Deine Rolle im Team

We are looking for a strong AI Data Engineer to help make HERE data AI-ready for the CoE's portfolio of use cases, building the pipelines, integrations, data products, and governed access patterns that enable AI solutions, agents, and automations to operate on trusted information.
This role works across enterprise systems, platforms, and business domains to resolve data quality, fragmentation, metadata, and access challenges that often prevent AI initiatives from moving beyond pilot stages into scalable production deployments.
As a critical member of the AI Center of Excellence, the AI Data Engineer transforms data readiness from a recurring executive concern into a measurable organizational capability, ensuring AI solutions are built on reliable, secure, and accessible data foundations.
Design, build, and maintain scalable data pipelines that support AI, machine learning, generative AI, and agent-based solutions.
Develop connectors and integrations across enterprise applications, databases, SaaS platforms, APIs, and knowledge repositories.
Create reusable data services and data products that accelerate AI use case delivery across the company.
Ensure AI systems can access high-quality, current, and trusted information through robust retrieval and integration patterns.
Partner with AI Solution Architects, Data Scientists, Product Owners, and Business Stakeholders to understand data requirements for AI use cases.
Design and implement architectures supporting agentic workflows, Retrieval-Augmented Generation (RAG), semantic search, and AI-driven automation.
Establish standardized patterns for structured and unstructured data ingestion, transformation, and access.
Support the transition of AI solutions from pilot initiatives to enterprise-scale production deployments.
Identify and resolve data quality, consistency, lineage, and ownership issues across business domains.
Implement monitoring, validation, and observability mechanisms to ensure data reliability.
Work with Security, Privacy, and Governance teams to ensure AI solutions comply with company policies and regulatory requirements.
Define and maintain metadata, cataloging, and governance standards that improve discoverability and trust in enterprise data.
Partner with business, technology, and data teams to prioritize data readiness initiatives supporting the AI roadmap.
Influence platform and application owners to adopt AI-friendly data practices.
Help establish enterprise best practices for AI data architecture, governance, and operational support.
Contribute to the broader AI CoE strategy by identifying systemic data challenges and recommending long-term solutions.

Unsere Erwartungen an dich

Ausbildung

Bachelor's/ Master's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field.

Qualifikationen

Strong understanding of data modeling, ETL/ELT processes, APIs, event-driven architectures, and data integration patterns.
Proficiency with SQL and at least one modern programming language such as Python, Java, or Scala.
Strong problem-solving skills and the ability to work across complex organizational environments.
Familiarity with vector databases, embeddings, semantic search, and Retrieval-Augmented Generation (RAG) architectures.
Understanding of data privacy, security, and responsible AI principles.
Knowledge of M365 Copilot, Copilot Studio, Azure AI Foundry, AWS Bedrock, or similar AI ecosystems.

Erfahrung

5+ years of experience in data engineering, integration engineering, or data platform development.
Experience designing and building enterprise-scale data pipelines using modern cloud and data platform technologies.
Experience working with both structured and unstructured data sources.
Experience working with AWS cloud platform and kubernetes.
Experience supporting AI, machine learning, generative AI, or agentic AI solutions.
Experience with data governance, metadata management, data catalogs, and data lineage tools.
Experience with modern orchestration and integration tools such as Airflow, Databricks, Snowflake, Azure Data Factory, Kafka, or similar platforms.
Experience building enterprise APIs and reusable data services.

Unser Angebot

Hybrid model of work.
Challenging problems to solve.
Collaborative and encouraging colleagues.
Opportunities to learn, grow and develop: company hackathons, technical talks, and trainings.
Regular feedbacks.
Paid vacation days.
A great work-life balance.
Flexible working hours.
Competitive salary plus bonus.
Medical coverage for you and your family (in Poland).
This role is eligible for Creative Tax Incentive scheme in Poland" or KUP (Autorskie Koszty Uzyskania Przychodu) (in Poland).
Option to work on a B2B contract (please note: benefits, bonus and KUP do not apply in this case- in Poland).
Diverse team of fantastic & talented people from 60+ countries worldwide.
Brown bag talks, team events, BBQ on the rooftop and more!